import os

import numpy as np
import tensorflow as tf
import matplotlib.pyplot as plt
from PIL import Image

from object_detection.utils import visualization_utils as vis_util
from object_detection.utils import label_map_util
NUM_CLASSES = 5



PATH_TO_CKPT = os.path.join('/content/models/research/quiz_w8_data/train_export', 'frozen_inference_graph.pb')
PATH_TO_LABELS = os.path.join('/content/models/research/quiz_w8_data', 'labels_items.pbtxt')

detection_graph = tf.Graph()
with detection_graph.as_default():
    od_graph_def = tf.GraphDef()
    with tf.gfile.GFile(PATH_TO_CKPT, 'rb') as fid:
        serialized_graph = fid.read()
        od_graph_def.ParseFromString(serialized_graph)
        tf.import_graph_def(od_graph_def, name='')

label_map = label_map_util.load_labelmap(PATH_TO_LABELS)
categories = label_map_util.convert_label_map_to_categories(label_map, max_num_classes=NUM_CLASSES, use_display_name=True)
category_index = label_map_util.create_category_index(categories)

def load_image_into_numpy_array(image):
    (im_width, im_height) = image.size
    return np.array(image.getdata()).reshape((im_height, im_width, 3)).astype(np.uint8)


test_img_path = os.path.join('/content/models/research/quiz_w8_data', 'test.jpg')

with detection_graph.as_default():
    with tf.Session(graph=detection_graph) as sess:
        image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
        detection_boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
        detection_scores = detection_graph.get_tensor_by_name('detection_scores:0')
        detection_classes = detection_graph.get_tensor_by_name('detection_classes:0')
        num_detections = detection_graph.get_tensor_by_name('num_detections:0')
        image = Image.open(test_img_path)
        image_np = load_image_into_numpy_array(image)
        image_np_expanded = np.expand_dims(image_np, axis=0)
        (boxes, scores, classes, num) = sess.run([detection_boxes, detection_scores, detection_classes, num_detections], 
            feed_dict={image_tensor: image_np_expanded})
        vis_util.visualize_boxes_and_labels_on_image_array(
            image_np,
            np.squeeze(boxes),
            np.squeeze(classes).astype(np.int32),
            np.squeeze(scores),
            category_index,
            use_normalized_coordinates=True,
            line_thickness=8)
        plt.imsave(os.path.join('/content/models/research/quiz_w8_data', 'test_result.png'), image_np)
        # plt.figure(figsize=IMAGE_SIZE)
        # plt.imshow(image_np)
        # plt.grid(b=None)
